text: import glob
  import pickle
  
  import cv2
  import numpy as np
  
  # Camera calibration and storing values in pickle
  # Prepare data for camera calibration
  def prepareCalibrationInputs():
      # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
      objp = np.zeros((6 * 9, 3), np.float32)
      objp[:, :2] = np.mgrid[0:9, 0:6].T.reshape(-1, 2)
  
      # Arrays to store object points and image points from all the images.
      objpoints = []  # 3d points in real world space
      imgpoints = []  # 2d points in image plane.
  
      # Make a list of calibration images
      images = glob.glob('../camera_cal/calibration*.jpg')
  
      # Step through the list and search for chessboard corners
      for fname in images:
          img = cv2.imread(fname)
          gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  
          # Find the chessboard corners
          ret, corners = cv2.findChessboardCorners(gray, (9, 6), None)
  
          # If found, add object points, image points
          if ret == True:
              objpoints.append(objp)
              imgpoints.append(corners)
  
              # Draw and display the corners
              img = cv2.drawChessboardCorners(img, (9, 6), corners, ret)
              cv2.imshow('img', img)
              cv2.waitKey(500)
              cv2.imwrite('../output_images/'+fname, img)
  
      cv2.destroyAllWindows()
      return objpoints, imgpoints
  
  
  #Call this function once and get data from pickle later.
  objpoints, imgpoints = prepareCalibrationInputs()
  
  mydict = {"objpoints": objpoints, "imgpoints": imgpoints}
  
  pickle.dump(mydict, open("cam_calibration_pickle.p", "wb"))
  
  